Huiping Jiang1,*, Demeng Wu1, Xingqun Tang1, Zhongjie Li1, Wenbo Wu2
CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2697-2712, 2022, DOI:10.32604/cmc.2022.027856
- 16 June 2022
Abstract Emotions serve various functions. The traditional emotion recognition methods are based primarily on readily accessible facial expressions, gestures, and voice signals. However, it is often challenging to ensure that these non-physical signals are valid and reliable in practical applications. Electroencephalogram (EEG) signals are more successful than other signal recognition methods in recognizing these characteristics in real-time since they are difficult to camouflage. Although EEG signals are commonly used in current emotional recognition research, the accuracy is low when using traditional methods. Therefore, this study presented an optimized hybrid pattern with an attention mechanism (FFT_CLA) for… More >
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